Blinks do not only protect the eye, but they do also correct for torsional eye position deviations by blink-associated resetting eye movements (BARMs). Although BARMs are functionally distinct from other eye movements in the torsional dimension, it has remained open if BARMs observed in the horizontal and vertical dimensions (fixational BARMs) are not simply microsaccades coinciding with blinks. We show here that fixational BARMs are functionally distinct and complementary to microsaccades in the following way: First, they compensate for large fixational error more efficiently than microsaccades, secondly, their probability to be executed in eccentric eye positions is higher, and thirdly, they reset the eyes into a position zone that is broader as compared to microsaccades. This suggests that BARMs help to keep the eyes in a working range wherein microsaccades guarantee high acuity vision. Moreover, we establish that fixational BARMs operate in a retina-centric frame.

The purpose of blinks is to keep the eyes hydrated and to protect them. Blinks are rarely noticed by the subject as blink-induced alterations of visual input are blanked out without jeopardizing the perception of visual continuity, features blinks share with saccades. Although not perceived, the blink-induced disconnection from the visual environment leads to a loss of information. Therefore there is critical need to minimize it. Here we demonstrate evidence for a new type of eye movement serving a distinct oculomotor demand, namely the resetting of eye torsion, likewise inevitably causing a loss of visual information. By integrating this eye movement into blinks, the inevitable down times of vision associated with each of the two behaviors are synchronized and the overall downtime minimized.DOI: http://dx.doi.org/10.7554/eLife.16290.001

Neural-Matrix style, high-density electrode arrays for brain-machine interfaces (BMIs) and neuroscientific research require the use of multiplexing: Each recording channel can be routed to one of several electrode sites on the array. This capability allows the user to flexibly distribute recording channels to the locations where the most desirable neural signals can be resolved. For example, in the Neuropixel probe, 960 electrodes can be addressed by 384 recording channels. However, currently no adaptive methods exist to use recorded neural data to optimize/customize the electrode selections per recording context. Here, we present an algorithm called classification-based selection (CBS) that optimizes the joint electrode selections for all recording channels so as to maximize isolation quality of detected neurons. We show, in experiments using Neuropixels in non-human primates, that this algorithm yields a similar number of isolated neurons as would be obtained if all electrodes were recorded simultaneously. Neuron counts were 41-85% improved over previously published electrode selection strategies. The neurons isolated from electrodes selected by CBS were a 73% match, by spike timing, to the complete set of recordable neurons around the probe. The electrodes selected by CBS exhibited higher average per-recording-channel signal-to-noise ratio. CBS, and selection optimization in general, could play an important role in development of neurotechnologies for BMI, as signal bandwidth becomes an increasingly limiting factor. Code and experimental data have been made available1.

11We try to deploy the retinal fovea to optimally scrutinize an object of interest by directing our eyes 12 to it. Horizontal and vertical components of these fixation eye movements are determined by the 13 object's location. However, fixation eye movements also involve a torsional component, which 14 according to Listing's law is fully determined by the 2D eye position acquired. According to Von 15 Helmholtz knowledge of the torsion provided by this law alleviates the perceptual interpretation 16 of the image tilt that changes with fixation, a view supported by psychophysical experiments he 17 pioneered. We address the question where and how Listing's law is implemented in the visual 18 system and we show that neurons in monkey area V1 use knowledge of torsion to compensate the 19 image tilt associated with specific eye positions as set by Listing's law. 20 65the actual experiment starting after several weeks of intensive training. Here we stopped presenting 66 the visual reference line, assuming that the monkey would now use an internal reference 67 corresponding to his subjective vertical. The results described below support the conclusion that 68